Work

An Analysis of Performance Variability in AWS Virtual Machines

Year: 2024

Type: conference-paper

Abstract: Cloud computing platforms are essential for a wide range of applications, including High-Performance Computing (HPC) and artificial intelligence. However, the performance variability of virtual machines (VMs) in these shared environments presents significant challenges. This paper provides an extensive month-long analysis of the performance variability of C family VMs on Amazon Web Services (AWS) across two regions (us-east-1 and sa-east-1), various instance generations, and market types. Our findings indicate that Graviton processors (c6g.12xlarge and c7g.12xlarge) exhibit minimal performance variability and high cost-effectiveness, with the c7g.12xlarge instance, in particular, offering significantly reduced execution times and lower costs. Intel and AMD instances, while showing performance improvements from generation c6 to c7, exhibited up to 20% variability.

DOI: 10.5753/sscad.2024.244526

Authors: Miguel de Lima, Luan Teylo, Lúcia Drummond

Institutions: Universidade Federal Fluminense, Université de Bordeaux, Centre Inria de l'université de Bordeaux, TADAAM: Gestion des données à l'échelle du système en fonction de la topologie pour le calcul haute performance

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico

OpenAlex ID: W4403757796

FWCI: 1.537

Cites: 10

Cited by: 4

Related to: 10